Title :
Optimal subarray size for spatial smoothing
Author :
Gershman, Alex B. ; Ermolaev, Victor T.
Author_Institution :
Signal Process. Lab., Swiss Federal Inst. of Technol., Lausanne, Switzerland
Abstract :
We consider the popular spatial smoothing technique and show via the covariance matrix eigenvalue analysis that the simple suboptimal rule for choosing of the subarray size exists in a practically important situation of two coherent equipower closely spaced sources. This rule has been derived by maximizing the distance between the signal subspace and the noise subspace eigenvalues of spatially smoothed covariance matrix and it does not require any a priori information about the signal source parameters.<>
Keywords :
array signal processing; covariance analysis; covariance matrices; eigenvalues and eigenfunctions; linear antenna arrays; smoothing methods; coherent equipower closely spaced sources; covariance matrix; eigenvalue analysis; noise subspace; optimal subarray size; signal subspace; spatial smoothing; suboptimal rule; uniform linear array; Apertures; Covariance matrix; Decorrelation; Eigenvalues and eigenfunctions; Sensor arrays; Signal generators; Smoothing methods; Spatial coherence; Spatial resolution;
Journal_Title :
Signal Processing Letters, IEEE
